Silicon Infrastructure Engineer, TPU, Google Cloud

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at a scale, and extend well beyond web search. We are looking for engineers who bring ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.

We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

Minimum qualifications:

• Bachelor's degree in Electrical Engineering or equivalent practical experience.
• Experience with programming or scripting (e.g., C, C++, Perl, TCL, Python), and working with debug tools (e.g., Verdi, SimVision/Indago, gdb) to support methodology and automation work.
• Experience with associated EDA tools and the addition of automation and flow enhancements.

Preferred qualifications:

• Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
• Experience deploying EDA tools into distributed environments and supporting their efficient usage.
• Experience with RTL design, Verilog and simulation (VCS, Incisive, Questa), and System Verilog (DPI and transactors), assertions.
• Familiarity with system administration, networking, and security systems.